Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

DLpTCR: an ensemble deep learning framework for predicting immunogenic peptide recognized by T cell receptor
Zhaochun Xu, Meng Luo, Wei‐Zhong Lin, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 73

Showing 1-25 of 73 citing articles:

Therapeutic cancer vaccines: advancements, challenges and prospects
Ting Fan, Mingna Zhang, Jingxian Yang, et al.
Signal Transduction and Targeted Therapy (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 179
Pan-Peptide Meta Learning for T-cell receptor–antigen binding recognition
Yicheng Gao, Yuli Gao, Yuxiao Fan, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 3, pp. 236-249
Open Access | Times Cited: 84
Bitter-RF: A random forest machine model for recognizing bitter peptides
Yufei Zhang, Yuhao Wang, Zhi-Feng Gu, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 40
Development and use of machine learning algorithms in vaccine target selection
Barbara Bravi
npj Vaccines (2024) Vol. 9, Iss. 1
Open Access | Times Cited: 30
Informing immunotherapy with multi-omics driven machine learning
Yawei Li, Wu Xin, Deyu Fang, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 19
TULIP: A transformer-based unsupervised language model for interacting peptides and T cell receptors that generalizes to unseen epitopes
Barthelemy Meynard-Piganeau, Christoph Feinauer, Martin Weigt, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 24
Open Access | Times Cited: 16
Neoantigen-targeted TCR-engineered T cell immunotherapy: current advances and challenges
Zhi Pang, Manman Lu, Yu Zhang, et al.
Biomarker Research (2023) Vol. 11, Iss. 1
Open Access | Times Cited: 26
A unified cross-attention model for predicting antigen binding specificity to both HLA and TCR molecules
Chenpeng Yu, Xing Fang, Shiye Tian, et al.
Nature Machine Intelligence (2025)
Closed Access | Times Cited: 1
EnANNDeep: An Ensemble-based lncRNA–protein Interaction Prediction Framework with Adaptive k-Nearest Neighbor Classifier and Deep Models
Lihong Peng, Jingwei Tan, Xiongfei Tian, et al.
Interdisciplinary Sciences Computational Life Sciences (2022) Vol. 14, Iss. 1, pp. 209-232
Closed Access | Times Cited: 35
Neoantigens in precision cancer immunotherapy: from identification to clinical applications
Qiao Zhang, Qingzhu Jia, Jing Zhang, et al.
Chinese Medical Journal (2022) Vol. 135, Iss. 11, pp. 1285-1298
Open Access | Times Cited: 28
Performance comparison of TCR-pMHC prediction tools reveals a strong data dependency
Lihua Deng, Cedric Ly, Sina Abdollahi, et al.
Frontiers in Immunology (2023) Vol. 14
Open Access | Times Cited: 21
TULIP — a Transformer based Unsupervised Language model for Interacting Peptides and T-cell receptors that generalizes to unseen epitopes
Barthelemy Meynard-Piganeau, Christoph Feinauer, Martin Weigt, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 18
Pep-CNN: An improved convolutional neural network for predicting therapeutic peptides
Shengli Zhang, Xinjie Li
Chemometrics and Intelligent Laboratory Systems (2022) Vol. 221, pp. 104490-104490
Closed Access | Times Cited: 23
dbPepNeo2.0: A Database for Human Tumor Neoantigen Peptides From Mass Spectrometry and TCR Recognition
Manman Lu, Linfeng Xu, Xingxing Jian, et al.
Frontiers in Immunology (2022) Vol. 13
Open Access | Times Cited: 23
BERTrand—peptide:TCR binding prediction using Bidirectional Encoder Representations from Transformers augmented with random TCR pairing
Alexander Myronov, Giovanni Mazzocco, Paulina Król, et al.
Bioinformatics (2023) Vol. 39, Iss. 8
Open Access | Times Cited: 13
T-cell receptor binding prediction: A machine learning revolution
Anna Weber, Aurélien Pélissier, María Rodríguez Martínez
ImmunoInformatics (2024) Vol. 15, pp. 100040-100040
Open Access | Times Cited: 5
Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy
Alla Bulashevska, Zsófia Nacsa, Franziska Lang, et al.
Frontiers in Immunology (2024) Vol. 15
Open Access | Times Cited: 4
HEDDI-Net: heterogeneous network embedding for drug-disease association prediction and drug repurposing, with application to Alzheimer’s disease
Yin-Yuan Su, Hsuan‐Cheng Huang, Yu‐Ting Lin, et al.
Journal of Translational Medicine (2025) Vol. 23, Iss. 1
Open Access
A unified deep framework for peptide–major histocompatibility complex–T cell receptor binding prediction
Yunxiang Zhao, Jijun Yu, Yixin Su, et al.
Nature Machine Intelligence (2025)
Open Access
TEPCAM: Prediction of T‐cell receptor–epitope binding specificity via interpretable deep learning
Junwei Chen, Bowen Zhao, Shenggeng Lin, et al.
Protein Science (2023) Vol. 33, Iss. 1
Closed Access | Times Cited: 11
Neoantigen cancer vaccines: a new star on the horizon
Xiaoling Li, Jian You, Liping Hong, et al.
Cancer Biology and Medicine (2023), pp. 1-38
Open Access | Times Cited: 11
Empirical comparison and recent advances of computational prediction of hormone binding proteins using machine learning methods
Hasan Zulfiqar, Zhiling Guo, Bakanina Kissanga Grace-Mercure, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 21, pp. 2253-2261
Open Access | Times Cited: 10
Attention network for predicting T-cell receptor–peptide binding can associate attention with interpretable protein structural properties
Kyohei Koyama, Kosuke Hashimoto, Chioko Nagao, et al.
Frontiers in Bioinformatics (2023) Vol. 3
Open Access | Times Cited: 9
The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood
Yideng Cai, Meng Luo, Wenyi Yang, et al.
Cancer Research (2024) Vol. 84, Iss. 11, pp. 1915-1928
Closed Access | Times Cited: 3
Sliding-attention transformer neural architecture for predicting T cell receptor–antigen–human leucocyte antigen binding
Ziyan Feng, Jingyang Chen, Youlong Hai, et al.
Nature Machine Intelligence (2024)
Open Access | Times Cited: 3
Page 1 - Next Page

Scroll to top